A Model-Based Approach to Predict Short-Term Toxicity Benefits With Proton Therapy for
Oropharyngeal Cancer
Rwigema, Jean-Claude M.; Langendijk, Johannes A.; van der Laan, Hans Paul; Lukens, John
N.; Swisher-McClure, Samuel D.; Lin, Alexander
Published in:
International Journal of Radiation Oncology, Biology, Physics DOI:
10.1016/j.ijrobp.2018.12.055
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Rwigema, J-C. M., Langendijk, J. A., van der Laan, H. P., Lukens, J. N., Swisher-McClure, S. D., & Lin, A. (2019). A Model-Based Approach to Predict Short-Term Toxicity Benefits With Proton Therapy for
Oropharyngeal Cancer. International Journal of Radiation Oncology, Biology, Physics, 104(3), 553-562. https://doi.org/10.1016/j.ijrobp.2018.12.055
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A model-based approach to predict short-term toxicity benefits with proton therapy for oropharyngeal cancer
Jean-Claude M. Rwigema, M.D., Johannes A. Langendijk, M.D. Ph.D., Hans Paul van der Laan, Ph.D., John N. Lukens, M.D., Samuel D. Swisher-McClure, M.D., Alexander Lin, M.D.
PII: S0360-3016(19)30002-1
DOI: https://doi.org/10.1016/j.ijrobp.2018.12.055 Reference: ROB 25487
To appear in: International Journal of Radiation Oncology • Biology • Physics Received Date: 29 May 2018
Revised Date: 11 December 2018 Accepted Date: 20 December 2018
Please cite this article as: Rwigema J-CM, Langendijk JA, Paul van der Laan H, Lukens JN, Swisher-McClure SD, Lin A, A model-based approach to predict short-term toxicity benefits with proton therapy for oropharyngeal cancer, International Journal of Radiation Oncology • Biology • Physics (2019), doi: https://doi.org/10.1016/j.ijrobp.2018.12.055.
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1A model-based approach to predict short-term toxicity benefits with proton therapy for oropharyngeal cancer
Jean-Claude M. Rwigema M.D.1,2, Johannes A. Langendijk M.D. Ph.D.3, Hans Paul van der Laan Ph.D.3, John N. Lukens M.D.1, Samuel D. Swisher-McClure M.D.1, Alexander Lin M.D.1
1
Perelman School of Medicine, University of Pennsylvania, Department of Radiation Oncology, Philadelphia, PA; 2Mayo Clinic, Department of Radiation Oncology, Phoenix, AZ; 3 Department of Radiation Oncology, University of Groningen, University Medical Center Groningen, Groningen, Netherlands
Short title: Predictive outcomes model for proton therapy in oropharyngeal cancer.
Corresponding Author:
Alexander Lin M.D.
Department of Radiation Oncology
Perelman School of Medicine, University of Pennsylvania
3400 Civic Center Blvd
Philadelphia, PA 19104
Email: alexander.lin@uphs.upenn.edu.
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1 AbstractPurpose: The aim of this study was to generate normal tissue complication probability (NTCP) models in patients treated with either proton beam therapy (PBT) or intensity-modulated radiotherapy (IMRT) for
oropharynx cancer, and to use a model-based approach to investigate the added value of PBT in
preventing treatment complications.
Methods: For patients with advanced-stage oropharynx cancer, treated with curative intent (PBT, n=30; IMRT, n=175), NTCP models were developed using multivariable logistic regression analysis with
backward selection. For PBT-treated patients, an equivalent IMRT plan was generated, to serve as a
reference to determine the benefit of PBT in terms of NTCP. The models were then applied to the PBT
treated patients to compare predicted and observed clinical outcomes (calibration-in-the large). Five
binary endpoints were analyzed at 6-months post-treatment: dysphagia ≥ grade 2, dysphagia ≥ grade 3,
xerostomia ≥ grade 2, salivary duct inflammation ≥ grade 2, and feeding tube dependence. Corresponding
toxicity grading was based on CTCAEv4. Paired t-tests and Wilcoxon rank tests were used to compare
mean NTCP results for endpoints between PBT and IMRT.
Results: NTCP models developed based on outcomes from all patients were applied to those receiving PBT. NTCP-values were calculated for the equivalent IMRT plans for all PBT treated patients, revealing
significantly higher NTCP-values with IMRT. PBT was associated with statistically significant reductions
in the mean NTCP values for each endpoint at 6-months post treatment, with the largest absolute
differences in rates of > grade 2 dysphagia and > grade 2 xerostomia.
Conclusion: NTCP models predict significant improvements in the probability of short-term, treatment-related toxicity with PBT compared to IMRT for oropharyngeal cancer. This study demonstrated an
NTCP model-based approach to compare predicted patient outcomes when randomized data are not
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2Key words: Oropharyngeal cancer, NTCP, toxicity, IMRT, proton therapy, head and neck cancer
INTRODUCTION
Currently most patients diagnosed with oropharyngeal head and neck carcinoma are cured after
undergoing definitive multimodality therapy [1, 2]. Despite technological advances in head and neck
radiotherapy, many patients experience long-term severe toxicities that negatively impact quality of life
[3-7].
Data from single institution series have demonstrated advantages of proton beam therapy (PBT)
over intensity-modulated radiotherapy (IMRT), due to PBT’s favorable dose deposition beam profile that
improves sparing of organs at risk and reduces integral dose to the patient [8-12]. As a result, randomized
trials are ongoing to provide level I evidence regarding the clinical benefit of PBT [13]. Completing
comparative randomized trials for new treatment technology remains challenging due to pre-existing
patient preferences for selected treatments, high costs of conducting research, and potential ethical
considerations related to clinician equipoise [14]. Moreover, in an era of personalized medicine with
ever-increasing patient and tumor data heterogeneity, traditional level I evidence may not always
adequately support individualized clinical decision making [15]. Data derived from statistical modeling of
clinical outcomes for individual patients, can provide complementary data regarding the comparative
effectiveness of treatment approaches in question. A model-based approach may be a cost-effective
strategy to quantify clinical gains with PBT via estimation of potential reduction in normal tissue
complication probability (NTCP) [16]. Such an approach may be optimal in informing patient eligibility
for a chosen therapy to enhance clinical outcomes and cost efficiency [17].
To date, only one study evaluated NTCP models for PBT in a heterogeneous group of head and
neck patients [18]. The aim of this study was to generate multivariable normal tissue complication
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3hypothesize that improvements in dosimetric normal tissue sparing with PBT will translate to lower
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4 METHODS AND MATERIALSStudy population
This (institution review board approved) study included patients with locally-advanced
oropharyngeal carcinoma treated with curative intent multi-modality therapy from two institutions who
had at least one year of follow-up. The cohort from the XXXXX consisted of 30 patients with
oropharyngeal carcinoma treated with surgery followed by adjuvant proton radiotherapy, with or without
chemotherapy (decision to offer chemotherapy was consistent with standard of care, such as the presence
of positive margin and/or extranodal extension [19]) between 2013 and 2016. The cohort from the
XXXXXX consisted of 175 patients mainly with locally-advanced oropharyngeal carcinoma treated with
definitive photon radiotherapy with or without chemotherapy..
Treatment
Patients in the postoperative cohort from XXXXX underwent radiotherapy planning at
approximately 3-4 weeks after surgery. The process of computed tomography (CT) simulation
acquisition, target delineation and treatment planning has been previously described [9]. For these
patients, PBT plans (which were the ones clinically delivered to the patients) were generated for treatment
delivery using pencil-beam scanning (PBS) via single field uniform dosing, plus an accompanying IMRT
(VMAT) plan which was clinically reviewed and deemed acceptable for treatment (but not delivered, as
they were reserved as a contingency plan only in case of unexpected proton beam unavailability) [9].
These accompanying IMRT plans needed to meet all of the coverage goals and organ sparing constraints
similar to patients who receive the entirety of their radiotherapy via IMRT. For patients receiving
organ-preservation RT at XXXXX, photon plans were generated and delivered using IMRT as previously
described [20].
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5 Dosimetric data collection and extractionFor each patient, relevant organs-at-risk (OARs) were contoured as previously described [21, 22].
Target delineation was consistent with standard of care in both postoperative and definitive RT patients,
and no patients were enrolled or treated on protocols involving omission or reduction of standardly
defined clinical targets. OARs were bilateral parotid glands, inferior, middle and superior pharyngeal
constrictor muscles (PCM), supraglottic larynx, and oral cavity. All plans and structures were centrally
reviewed and modified as needed to reflect uniformity and consistency across both institutions. The
following dose volume histogram (DVH) parameters were collected for OARs: minimum dose, maximum
dose, mean dose, V5Gy, V10Gy, V20Gy, V30Gy, V40Gy, V50Gy, V60Gy and V70Gy (percent volume
receiving 5Gy, 10 Gy, 20 Gy, 30 Gy, 40 Gy, 50 Gy, 60 Gy and 70 Gy). DVH parameters were extracted
by MIRADA-software (Oxford Centre for Innovation UK) from both the XXXX PBT and IMRT plans
and then combined with XXXX IMRT plans for analysis.
Follow-up
After completion of therapy, patients were followed with clinical examinations and head and neck
imaging, initially with a 3-month post-treatment PET-CT, then PET-CT or CT every 3-6 months for the
first 2 years, and then every 6-12 months thereafter. Toxicity data was collected before the start of
radiotherapy and at every follow-up visit and graded using CTCAE version 4.0.
Endpoints
The following toxicity endpoints were defined at 6 months from treatment completion: (1)
Dysphagia ≥ grade 2; (2) dysphagia ≥ grade 3; (3) xerostomia ≥ grade 2; (4) salivary duct inflammation ≥
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61 = slightly thickened saliva; slightly altered taste; Grade 2 = thick, ropy, sticky saliva; markedly altered
taste; alteration in diet indicated; secretion-induced symptoms; limiting instrumental activities of daily
living (ADL); Grade 3 = acute salivary gland necrosis; sever secretion-induced symptoms; tube feeding
indicated; limiting self-care ADL; disabling; Grade 4 = life-threatening consequences; urgent intervention
indicated; Grade 5 = death.
The 6-month endpoint was chosen, given that this was the time point for which the largest amount of
toxicity data existed for all patients. All toxicity endpoints were collected and documented prospectively.
Statistics
Patients who had one of the endpoints already at baseline, were excluded from the analyses
regarding that particular endpoint. For each endpoint, multivariable NTCP models were created.
Univariable logistic regression analyses and correlation statistics were performed to select candidate
predictors for each endpoint that were significantly associated with the endpoints in univariable analysis
(p < 0.05), but not mutually correlated (r < 0.80). Then, a stepwise backward multivariable logistic
regression procedure was used to exclude the variables with p > 0.157 from the model. The resulting
model was then manually explored further in two ways: 1) by testing whether the models would
significantly deteriorate when one or more variables would be removed; 2) by exchanging the selected
dose volume variables by other potentially relevant dose variables that were highly correlated to the
selected dose variable and therefore discarded in an earlier stage. The final best model was chosen
primarily by the applying the likelihood-ratio test, but also by evaluating the general model performance
measures, i.e., ROC-area under the curve, discrimination slope, explained variance and calibration. For
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7correct (shrink) the models (slope and intercept) for optimism. This was done to obtain realistic regression
coefficients for the model variables that are representative for populations like the development sample. A
figure summarizing the steps in model generation is shown in Figure 1.
Candidate variables that were initially entered in the model were: gender (male versus female),
age (as continuous variable), concomitant chemotherapy (no vs. yes), weight loss at baseline (0-10 vs.
>10%), accelerated radiotherapy (no vs. yes), T-stage (stage 1-2 vs. 3-4), N-stage (negative vs. positive),
target volume (local/unilateral vs. bilateral neck irradiation), surgery (no vs. yes), and baseline toxicities
(grade 0 vs. grade 1). Paired t-tests and Wilcoxon rank tests were used to compare mean NTCP results for
endpoints between PBT and IMRT. Data were analyzed using SPSS Statistics for Windows, version 23.
NTCP calculation
NTCP values were determined for each patient at all endpoints in both PBT and photon plans using the
NTCP formulae [23]: NTCP =
( ) with the linear predictor (S) for complications defined as:
= + ∑ ∙
where (intercept) and (variable coefficients)were the model parameters and the predictor variables.
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8 RESULTSPatient and treatment characteristics, observed rates of toxicities at 6-months with corresponding OAR
mean doses for relevant endpoints of the 2 patient cohorts are shown in Table 1. The difference in
increased sparing of an organ at risk, such as the oral cavity, is shown in Figure 2. A summary of all
model performance results for all endpoints is shown in Table 2, which presents the uncorrected
(apparent) modeling results, with uncorrected regression coefficients.
The final NTCP models for the endpoints below were developed based on outcomes of each endpoint
from all patients, and include the corrected coefficients (after internal validation).
(1) Dysphagia ≥ grade 2 at 6 months: S= -4.3477 + (0.0345 * contralateral parotid mean dose (Gy))
+ (0.0524 * oral cavity mean dose (Gy)).
(2) Dysphagia ≥ grade 3 at 6 months: S= -4.3188 + (1.3744 * T3 or 4) + (1.0222 * baseline weight
loss >10%) + (0.0385 * oral cavity mean dose (Gy)).
(3) Xerostomia ≥ grade 2 at 6 months: S= -3.6891 + (0.8639 * baseline xerostomia grade 1) +
(0.6423* concomitant chemotherapy) + (0.0520 * oral cavity mean dose (Gy)).
(4) Salivary Duct Inflammation ≥ grade 2 at 6 months: S= -6.3436 + (0.0389 * Age (years)) +
(1.0231* accelerated radiotherapy) + (0.0367 * oral cavity mean dose (Gy)).
(5) Tube feeding dependence at 6 months: S= -10.3690 + (1.3848 * T3 or 4) + (1.3805* baseline
weight loss >10%) + (0.0364 * PCM inferior mean dose (Gy)) + (0.0939* PCM superior mean
dose (Gy)).
The NTCP-values were calculated for the equivalent IMRT plans for all PBT treated patients, revealing
significantly higher NTCP-values for the IMRT plans for all endpoints (Table 3). PBT was associated
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9post treatment, with the largest absolute differences in rates of > grade 2 dysphagia and xerostomia
(Table 3). The absolute reductions in individual patient NTCP by PBT as compared to IMRT ranged
from 2 to 14% for grade 2 dysphagia, 1 to 8% for grade 3 dysphagia, 2 to 17% for grade 2 xerostomia, 1
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10 DISCUSSIONAlthough IMRT has led to reduction of radiation induced side effects with improved global
quality of life from 3D-conformal techniques, efforts are still needed to further enhance the therapeutic
ratio in oropharyngeal carcinoma after multimodality curative therapy [24-27]. It is for this reason that
proton therapy, with its ability to improve normal tissue sparing when compared to IMRT, may help to
improve patient toxicity outcomes and long-term quality of life. However, precise estimates of the clinical
impact of PBT are lacking with the current absence of randomized data. The present study evaluates
toxicity outcomes between IMRT to PBT using normal tissue complication probability models in order to
estimate potential clinical benefits of PBT using a large cohort of patients receiving radiotherapy for
oropharyngeal carcinoma.
Our study extends the existing literature regarding the comparative effectiveness of PBT for head
and neck radiotherapy and is the first report of such a comparative analysis limited to patients with
oropharynx cancer, in whom high rates of long-term survival emphasize a focus on toxicity mitigation to
preserve quality of life [1, 28]. Treatment-related late complications that commonly affect quality of life
in these patients are mainly dysphagia, gastrostomy-tube dependence, and xerostomia [29, 30]. In this
study, NTCP models were developed using patient cohorts from 2 institutions treated with IMRT and
PBT, respectively. The NTCP models were then applied to all patients receiving PBT, for whom each had
a treatment-approved ‘backup’ IMRT plan. Thus, each PBT patient served as an internal control when
comparing estimated toxicity from PBT vs IMRT, which we believe to be a unique strength of the study.
Four toxicity domains (ie. dysphagia, xerostomia, salivary duct inflammation, and G-tube dependence)
were evaluated and modeled at 6 months from completion of PBT. Results herein demonstrated
significant reduction of predicted complications in all evaluated head and neck treatment-related
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11With the introduction of new technologies in radiation delivery, coupled with its potential significant
costs, it is important to assess and confirm that new technologies for radiation delivery will lead to
meaningful gains for patients. The gold standard for such an effort remains a prospective, randomized
trial; however, barriers to successful implementation of such a trial exist, and will likely remain for
current and future efforts. Our study represents a novel approach that can be used currently to assess
potential benefits while we await the results of prospective trials.
This study has some limitations to warrant mention. First, even though our data suggests that
proton therapy may be a method by which treatment-related toxicity can be improved, it does not
specifically address the issue of cost effectiveness. The issue of cost effectiveness and justification of new
technologies is a much more complex issue, which is outside the limits of this study, and will have to be
addressed by future, collective efforts. Second, the PBT cohort was limited to only 30 patients, and the
cohorts from each institution were dissimilar in that one institution largely treated patients with an initial
surgical approach followed by adjuvant radiotherapy (+/- chemotherapy), while the other institution
largely treated patients with multimodality organ preservation. We acknowledge that the different
approaches may itself affect patient toxicity outcomes. However, our model was generated using data
and outcomes from the entire cohort from both institutions, incorporating patients receiving a range of
accepted treatment approaches, which may allow for this model to be generalizable for allowable
treatment approaches. Finally, our model overpredicted the rate of xerostomia compared to observed
prevalence for patients receiving proton therapy. While we would prefer, given a choice, that such models
overpredict rather than underpredict toxicity for proton therapy, it is clear that clinical validation of this
model in a larger group of patients, receiving a range of accepted treatment approaches, is needed. This is
already in progress, as patients at one of the participating institutions in this study is selecting and treating
patients with proton therapy for oropharynx cancer based on these models. The results and clinical
validation from current patient treatments will be a natural follow-up to this initial effort, and will be
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12In summary, this study demonstrates the potential value of NTCP model based approaches in
comparing predicted patient outcomes. Such a tool may be highly useful when randomized data are not
available, or when deciding on which patients may be most likely to benefit from the use of a limited
resource. Results of the current study may serve as a guide to patient selection, and provide
complementary data regarding estimated clinical effectiveness of PTV when results from properly
conducted phase III trials are not available [13, 14]. A model-based approach can also be incorporated
into the context of a prospective, randomized trial, either as a potential outcome biomarker, or as criteria
to best select patients for trial enrollment. In the end, we as radiation oncologists believe that our mission
is to improve the lives of our patients, and to apply advances in our field in a feasible and judicious
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16 Figure legendsFigure 1: Variable selection and logistic regression modeling for each endpoint
Figure 2: IMRT vs. PBT Comparison: axial (left) and sagittal (right) slices of representative radiation
plans for adjuvant radiation therapy in a patient with T1N2aM0 stage IVA (7th edition) base of tongue
carcinoma, showing IMRT and PBT radiation plans (60Gy in 30 fractions) for the same patient. The PBT
plan demonstrates lower dose to oral cavity structures compared to IMRT.
Figure 3. Waterfall plots showing illustrating individual reduction in NTCP for (A) Dysphagia grade ≥2,
(B) Dysphagia grade ≥3, (C) Xerostomia ≥grade 2, (D) Salivary duct inflammation grade ≥2, and (E)
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Table 1Proton cohort (n=30) Photon cohort (n=175)
Number % Number % *SMD p value
Neck RT Bilateral 29 96.70% 155 88.60% -0.31 0.05 Male 26 86.70% 112 64.00% -0.55 0.003 Robotic Surgery Primary Site 29 96.70% 0 0.00% -7.66 < 0.001 Extensive Surgery Primary Site* 1 3.30% 1 0.60% -0.20 0.42 Surgery neck* 30 100.00% 3 1.70% -10.75 < 0.001 Concomitant chemotherapy 7 23.30% 101 57.70% 0.75 < 0.001 T3 or T4 5 16.70% 90 51.40% 0.79 < 0.001 Node positive 29 96.70% 135 77.60% -0.60 < 0.001 Pre-Treatment Weight loss >10% 2 6.70% 14 8.40% 0.06 0.75 Accelerated (6
fraction per week) RT 3 10.00% 54 30.90% 0.54 0.002 Dysphagia CTCAEv4 ≥G2 at Baseline 0 0.00% 46 26.30% 0.84 < 0.001 Dysphagia CTCAEv4 ≥G2 at 6 Months 2 6.70% 84 48.00% 1.04 < 0.001 Dysphagia CTCAEv4 ≥G3 at 6 Months 1 3.30% 47 26.90% 0.70 < 0.001
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Xerostomia CTCAEv4 ≥G1 at Baseline 4 13.30% 24 13.70% 0.01 0.96 Xerostomia CTCAEv4 ≥G2 at 6 Months 0 0.00% 80 46.20% 1.31 < 0.001 Salivary Duct Inflammation CTCAEv4 ≥G1 at Baseline 1 3.30% 23 13.10% 0.36 0.02 Salivary Duct Inflammation CTCAEv4 ≥G2 at 6 Months 1 3.30% 31 17.90% 0.49 0.001 Tube feeding dependence at 6 months 0 0.00% 36 20.60% 0.72 < 0.001 AVERAGE VALUES Age (years) 58.2 ± 11.8 60.1 ± 8.7 0.18 0.40 High Risk PTV Prescribed dose (Gy) 62.2 ± 2.7 69.8 ± 2.2 3.09 < 0.001 Parotid ipsilateralmean dose (Gy) 32.4 ± 7.0 41.2 ± 11.9 0.90
< 0.001 Parotid contralateral mean dose (Gy) 13.6 ± 5.7 29.1 ± 10.6 1.82 < 0.001 PCM inferior
mean dose (Gy) 29.1 ± 6.6 47.0 ± 13.0 1.74 < 0.001
PCM superior
mean dose (Gy) 43.0 ± 6.8 62.7 ± 7.1 2.83
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Oral cavity mean
dose (Gy) 22.3 ± 9.5 56.3 ± 7.6 3.95
< 0.001
RT=radiotherapy; G2/3=grade 2 or 3 common toxicity Common Terminology Criteria for Adverse Events (CTCAE) Version 4.0; PTV=planning tumor volume; PCM=pharyngeal constrictor muscles; SMD = standardized mean difference
* In the photon cohort, 1 patient received open (non-robotic ) surgery to the primary site (without neck surgery), 3 patients received neck surgery without surgery to the primary tumor.
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TABLE 2. Model Summary Results
Measures (at 6 months) >G2 Dysphagia >G3 Dysphagia >G2 Xerostomia >G2 Salivary Duct Inflammation Tube Dependence Events Controls 107 147 118 163 162 Events* 52 (33%) 37 (20%) 76 (39%) 31 (16%) 34 (17%) Overall Nagelkerke adjusted R2 0.206 0.248 0.204 0.140 0.403 Discrimination ROC-curve AUC (95% CI) 0.750 (0.669-0.830) 0.783 (0.701-0.864) 0.713 (0.642-0.785) 0.710 (0.606-0.808) 0.864 (0.800-0.928) Discrimination slope 0.152 0.179 0.142 0.089 0.298 Calibration Hosmer-Lemeshow test X2 = 4.499 (p = 0.810) X2 = 10.769 (p = 0.216) X2 = 6.718 (p = 0.577) X2 = 4.483 (p = 0.810) X2 = 5.845 (p = 0.701) Validation / bootstrap Model slope correction 0.966 0.912 0.937 0.914 0.905 Model coefficients (uncorrected) Intercept -4.482 -4.595 -3.935 -6.813 -11.478 Oral cavity MD (Gy) 0.054 0.042 0.056 0.040 X Parotid cont. MD (Gy) 0.036 x x x X PCM sup MD (Gy) x x x x 0.105 PCM inf MD (Gy) x x x x 0.041 T3 or T4 x 1.492 x x 1.549 Weight loss BL >10% x 1.110 x x 1.544 Dry mouth BL Gr 1 x x 0.927 x x Concomitant chemo x x 0.689 x x
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Age (years) x x x 0.043 x Accelerated RT x x x 1.122 xROC=receiver operating curve; AUC=are under curve; R2=linear regression coefficient squared. MD=mean dose; PCM=pharyngeal constrictor muscles; sup=superior; inf=inferior; T=T stage; BL=at baseline; RT=radiotherapy; CI=confidence interval.
*Events are the patients in the whole dataset that had the endpoint at 6 months (i.e., the prevalence in the whole group). Both controls and those with events were part of the NTCP modeling, not just those with events.
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TABLE 3 Sig. (2-tailed) Sig. Endpoint Observed Prevalence (%) NTCP (Protons) NTCP (IMRT) Difference in mean/ gain (%) 95% Confidence Interval of the Difference in mean (gain) (%) t-test Wilcoxon (mean % + SD) (median %, range) (mean % + SD) (median %, range) Dysphagia grade ≥2 6.7 6.7 + 3.6 5.6 (2.2 - 17.7) 14.9 + 5.8 14.2 (5.2 - 31.2) -8.318 -9.431 -7.205 < 0.001 < 0.001 Dysphagia grade ≥3 3.3 4.9 + 4.4 3 (1.5 - 16.3) 7.6 + 5.7 5.3 (3.4 - 22) -2.694 -3.250 -2.137 < 0.001 < 0.001 Xerostomia grade ≥2 0 10.3 + 7.1 8.4 (3 - 39.7) 18.6 + 9.1 17.3 (8.4 - 50.4) -8.315 -9.613 -7.016 < 0.001 < 0.001 Salivary duct inflammation grade ≥2 3.3 4.7 + 3.3 3.8 (1.3 - 15.4) 7.6 + 4.7 6.1 (2.6 - 23.2) -2.857 -3.534 -2.180 < 0.001 < 0.001 Tube dependence 0 1.3 + 1.7 0.6 (0.1 - 6.2) 1.7 + 2.5 0.7 (0.1 - 11.1) -0.419 -0.890 0.052 0.079 0.005M
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Approaches to predict upfront the potential clinical gains of a new technology or approach in radiation delivery are needed in a rapidly advancing field. This study reports on an outcomes-based predictive model of anticipated gains (xerostomia and dysphagia) for proton therapy in the treatment of oropharynx cancer. These results and this approach can be used to complement prospective trials, or to rationalize novel treatment approaches when randomized data are not yet available.
